This study represents an initial effort to document nursing's unique contribution to patient outcomes. This project proposes the initial utilization and testing of an existing taxonomy, "Conditions that Necessitate Nursing Care" (CNNC) and its relationship to outcomes of critically ill patients. Critically ill patients require highly intensive and large quantities of nursing therapy. Although nursing care is responsible for the largest percentage of hospital resource consumption, the effect of nursing care on patient outcomes is virtually unknown. The taxonomy of nursing diagnoses represents the clinical judgments and decision-making of the nurse, and the corresponding prescriptive nursing treatments. The CNNC provides information regarding salient conditions in the patient that direct the provision of nursing care. Using a prospective approach, the appraisal of the CNNC taxonomy at multiple time points during the hospital experience will determine the efficacy or discrepancy of nursing care administered at different phases of hospitalization in achieving patient outcomes. Patients undergoing coronary artery bypass graft (CABG) surgery were selected as the target population for outcome assessment. The provision of care to patients undergoing coronary artery surgery accounts for one percent of the nation's health care spending. This study will examine the relationship between the need for nursing care as measured by the CNNC taxonomy and the standard outcomes of survival, length of stay, functional health status and quality of life (QOL). The taxonomy's effectiveness in predicting patient outcomes will be evaluated in 100 CABG patients at a 609 bed community hospital. Four time points will represent the change in nursing care needs trajectory: hospital admission, 24 hours after surgery, transfer from the surgical intensive care unit and day of discharge. FHS and QOL, will be measured at two time points: prior to surgery and 4-6 weeks after discharge from the hospital. Multiple regression will provide information on the CNNC categories that best predict outcomes of length of stay, functional health status and quality of life. Logistic regression will be used to predict the probability of survival. Trend analysis will be used to determine trends in the CNNC categories across the four phases of the open heart experience. This study tests the efficacy of utilization of a taxonomy representing nursing care provision for determining change in patient status. This study will provide health care institutions with an alternate method of assessing the effect of nursing services care on patient outcomes.